SER and throughput analysis of space–time analog network coded relaying system over shadowed Rician fading channels

Wireless Networks - This research article presents an innovative approach based on analog network coding (ANC) in conjunction with space time block coding (STBC) which is termed as space time...     

Collision Free Mobility Adaptive (CFMA) MAC for wireless sensor networks

In this paper we propose high throughput collision free, mobility adaptive and energy efficient medium access protocol (MAC) called Collision Free Mobility Adaptive (CFMA) for wireless sensor networks. CFMA ensures that transmissions incur no collisions, and allows nodes to undergo sleep mode whenever they are not transmitting or receiving. It uses delay allocation scheme based on traffic priority at each node and avoids allocating same backoff delay for more than one node unless they are in separate clusters. It also allows nodes to determine when they can switch to sleep mode during operation. CFMA for mobile nodes provides fast association between the mobile node and the cluster coordinator. The proposed MAC performs well in both static and mobile scenarios, which shows its significance over existing MAC protocols proposed for mobile applications. The performance of CFMA is evaluated through extensive simulation, analysis and comparison with other mobility aware MAC protocols. The results show that CFMA outperforms significantly the existing CSMA/CA, Sensor Mac (S-MAC), Mobile MAC (MOB-MAC), Adaptive Mobility MAC (AM-MAC), Mobility Sensor MAC (MS-MAC), Mobility aware Delay sensitive MAC (MD-MAC) and Dynamic Sensor MAC (DS-MAC) protocols including throughput, latency and energy consumption.     

Throughput-Oriented NoC Topology Generation and Analysis for High Performance SoCs

This paper presents a new approach to the design and analysis of NoC topologies which is based on the transaction-oriented communication methods of on-chip components. We propose two algorithms that attempt to meet the communication requirement of an on-chip application using a minimum number of network resources for the task, by generating application-specific topologies. In addition, to aid the design process of complex systems, the design method incorporates a form of predictive analysis which can estimate the degree of contention in a given system without performing detailed simulation. This predictive analysis method is used to determine the minimum frequency of operation for generated topologies, and is incorporated into the topology generation process. The proposed design method was tested using real-word applications, including an MPEG4 decoder and a multi-window display application. The generated topologies were found to offer similar or better performance when compared with regular topologies. However, the topologies generated by our method were more economical, using, on average, half the network resources of regular topologies.     

Personal identification using feature and score level fusion of palm- and fingerprints

The ever increasing demand of security has resulted in wide use of Biometric systems. Despite overcoming the traditional verification problems, the unimodal systems suffer from various challenges like intra class variation, noise in the sensor data etc, affecting the system performance. These problems are effectively handled by multimodal systems. In this paper, we present multimodal approach for palm- and fingerprints by feature level and score level fusions (sum and product rules). The proposed multi-modal systems are tested on a developed database consisting of 440 palm- and fingerprints each of 55 individuals. In feature level fusion, directional energy-based feature vectors of palm- and fingerprint identifiers are combined to form joint feature vector that is subsequently used to identify the individual using a distance classifier. In score level fusion, the matching scores of individual classifiers are fused by sum and product rules. Receiver operating characteristics curves are formed for unimodal and multimodal systems. Equal Error Rate (EER) of 0.538% for feature level fusion shows best performance compared to score level fusion of 0.6141 and 0.5482% of sum and product rules, respectively. Multimodal systems, however, significantly outperform unimodal palm- and fingerprints identifiers with EER of 2.822 and 2.553%, respectively.     

Direction of arrival estimation using adaptive directional time-frequency distributions

Time-frequency distributions (TFDs) allow direction of arrival (DOA) estimation algorithms to be used in scenarios when the total number of sources are more than the number of sensors. The performance of such time–frequency (t–f) based DOA estimation algorithms depends on the resolution of the underlying TFD as a higher resolution TFD leads to better separation of sources in the t–f domain. This paper presents a novel DOA estimation algorithm that uses the adaptive directional t–f distribution (ADTFD) for the analysis of close signal components. The ADTFD optimizes the direction of kernel at each point in the t–f domain to obtain a clear t–f representation, which is then exploited for DOA estimation. Moreover, the proposed methodology can also be applied for DOA estimation of sparse signals. Experimental results indicate that the proposed DOA algorithm based on the ADTFD outperforms other fixed and adaptive kernel based DOA algorithms.     

Finite-Impulse-Response Digital Differentiators for Midband Frequencies Based on Maximal Linearity Constraints

Maximally linear digital differentiators (DDs) are known for high accuracy in narrow frequency bands centered at the frequency for which they are designed. In this paper, designs of DDs of odd and even lengths having maximal linearity at the middle of the frequency band are presented. Applying the maximal linearity constraints to the magnitude response of a differentiator gives a system of linear equations, which can be solved for the impulse response coefficients of the differentiator. It is observed that the coefficient matrices of these equations are Vandermonde matrices, and this helps in finding the solution of the equations in closed form. Design examples are presented to show the accuracy of the presented designs, and it is observed that even-length designs are more accurate in a significantly wider frequency band as compared with odd-length designs     

Solution‐Processed Extremely Efficient Multicolor Perovskite Light‐Emitting Diodes Utilizing Doped Electron Transport Layer

A specially designed n‐type semiconductor consisting of Ca‐doped ZnO (CZO) nanoparticles is used as the electron transport layer (ETL) in high‐performance multicolor perovskite light‐emitting diodes (PeLEDs) fabricated using an all‐solution process. The band structure of the ZnO is tailored via Ca doping to create a cascade of conduction energy levels from the cathode to the perovskite. This energy band alignment significantly enhances conductivity and carrier mobility in the CZO ETL and enables controlled electron injection, giving rise to sub‐bandgap turn‐on voltages of 1.65 V for red emission, 1.8 V for yellow, and 2.2 V for green. The devices exhibit significantly improved luminance yields and external quantum efficiencies of, respectively, 19 cd A^?1 and 5.8% for red emission, 16 cd A^?1 and 4.2% for yellow, and 21 cd A^?1 and 6.2% for green. The power efficiencies of these multicolor devices demonstrated in this study, 30 lm W^?1 for green light‐emitting PeLED, 28 lm W^?1 for yellow, and 36 lm W^?1 for red are the highest to date reported. In addition, the perovskite layers are fabricated using a two‐step hot‐casting technique that affords highly continuous (>95% coverage) and pinhole‐free thin films. By virtue of the efficiency of the ETL and the uniformity of the perovskite film, high brightnesses of 10 100, 4200, and 16,060 cd m^?2 are demonstrated for red, yellow, and green PeLEDs, respectively. The strategy of using a tunable ETL in combination with a solution process pushes perovskite‐based materials a step closer to practical application in multicolor light‐emitting devices.     

Solid-State Synthesis and Thermoelectric Properties of Sb-Doped Mg2Si Materials

Sb-doped magnesium silicide compounds have been prepared through ball milling and solid-state reaction. Materials produced were near-stoichiometric. The structural modifications have been studied with powder x-ray diffraction. Highly dense pellets of Mg₂Si_1?x Sb _x (0 ≤ x ≤ 0.04) were fabricated via hot pressing and studied in terms of Seebeck coefficient, electrical and thermal conductivity, and free carrier concentration as a function of Sb concentration. Their thermoelectric performance in the high temperature range is presented, and the maximum value of the dimensionless figure of merit was found to be 0.46 at 810 K, for the Mg₂Si_0.915Sb_0.015 member.     

Determination of the average channel temperature of GaN MOSHFETs under continuous wave and periodic-pulsed RF operational conditions

We present a method to determine the average device channel temperature of AlGaN/GaN metal–oxide–semiconductor heterostructure field effect transistors (MOSHFETs) in the time domain under continuous wave (CW) and periodic-pulsed RF (radiation frequency) operational conditions. The temporal profiles of microwave output power densities of GaN MOSHFETs were measured at 2 GHz under such conditions and used for determination of the average channel temperature. The measurement technique in this work is also being utilized to determine the thermal time constant of the devices. Analytical temporal solutions of temperature profile in MOSHFETs are provided to support the method. The analytical solutions can also apply to generic field effect transistors (FETs) with an arbitrary form of time-dependent heat input at the top surface of the wafer. It is found that the average channel temperature of GaN MOSHFETs on a 300 μm sapphire substrate with the output power of 10 W/mm can be over 400 °C in the CW mode while the average channel temperature of GaN MOSHFETs on a SiC substrate with the same thickness only reaches 50 °C under the same condition. The highest average channel temperature in a pulsed RF mode will vary with respect to the duty cycle of the pulse and type of the substrate.     

Interaction of α radiation with iron-doped n-type silicon

Deep-level transient spectroscopy (DLTS) measurements were carried out on low-doped n-silicon before and after irradiation with 5.48 MeV α particles at room temperature with a fluence of 10¹⁰ α particles/cm². The DLTS measurements on the samples identified three electron levels E₁, E₂ and E₃ before irradiation. The deep-levels characteristic studies include emission rate signatures, activation energies, defect concentrations and capture cross sections. It was found that all pre-existing defects decreased their amplitudes during irradiation. The decrease in activation energy of level E₃ and noticeable suppression of level E₁ was also observed after irradiation. It was clearly seen that the composite peak E₃ (combination of E₂ and E₃) was successfully resolved after irradiating with α particles. α-irradiation is seen to lead a significant suppression of the iron interstitial defect, and without causing any change in its room temperature annealing characteristics.